Data Scientist Resume: 11+ Examples & Tips

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Data Scientist Resume (Text Version)

Contact Info:

John Matthews
[email protected]
1 (661) 593-0039
Los Angeles, CA 90011
linkedin.com/johnmatthews

Summary Statement:

Data Scientist: Experienced Data Scientist with IBM Certification. Skilled in problem solving and predictive analytics. Adept at working within highly collaborative environments, learning new methods, and adopting data science best practices. Demonstrable history of developing key business decision systems that foster business growth and expansion.

Key Accomplishments/Areas of Expertise

• SQL
• Python
• Shell Scripting
• Data Mining
• Analytics
• Detail Oriented
• Optimization
• Communication
• Efficient
•  

Professional Experience:

SLP Communications | Los Angeles, CA
Data Scientist | February 2016-Present

• Work with team of Data Scientists to solve problems and analyze data
• Employ predictive analytics and machine learning models to use data
• Collaborate with IT division to monitor model implementation
• Communicate with database using SQL
• Received awards for problem-solving and idea implementation

Brookside Leasing | Los Angeles, CA
Data Scientist | January 2013 – December 2015

• Developed evaluation approaches based on client needs
• Utilized Python software to explore data
• Analyzed new data sources for model improvements and optimization
• Applied statistical modeling to troubleshoot and solve problems
• Recommended business changes based upon exhaustive data analysis

UM Biotech | Los Angeles, CA
Data Scientist | September 2011 – December 2012

• Used shell scripting to create commands and execute program development
• Performed data regression analysis to increase company profitability
• Created new algorithms to streamline data analyses
• Implemented predictive analytics to determine product viability
• Met weekly with executives to discuss marketplace strategies

Education/Certifications

Bachelor of Arts, Computer Science
UC Berkeley, Berkeley, CA
Class of 2011

IBM Data Science Professional Certification
2012

A data scientist depends on software and computer languages to get the job done.

Structure and a set process are involved.

Similarly, a great resume is dependent upon key components and factors.

Formatting is very important!

It is growing ever more common for companies to scan resume submissions with software bots.

These bots look for certain keywords and language.

This practice is due to the large volume of resumes some companies and businesses receive. Bots are intended to weed out the strong resumes from the weak, or to select only the most relevant.

So it’s crucial that you use good keywords, language, and formatting.

When your resume does eventually reach the eyes of a hiring manager, he or she will only spend about 6 seconds reading it.

Another reason to get it right!

To obtain good readability, it is prudent to use a reverse chronological layout. This will ensure that your best skills and most recent position are seen first by the reader.

Pay attention to font selection as well. Don’t be careless and choose a random font. Rather, select one that is simple, looks professional, and is easy to read.

Also, make sure that your column, bullet point lists, and overall sections are aligned correctly on the page.

You want to present a resume with a clean and organized aesthetic.

Starting your resume off with a summary of your expertise is a great way to make an immediate impression – and that’s what you want.

So, using 2-3 sentences, sum up what makes you qualified for the position. Give a quick but detailed rundown of your key skill areas.

Don’t use generalities!

PRO TIP: It can be challenging to encapsulate your qualities in just a few short sentences. So really consider your chief areas and skills. Also ask yourself what type of Data Scientist you are. Skilled? Experienced? Dependable? Answering these questions will help you get started.

Now let’s have a look at some summary examples:

One example displays a high level of competency and a dependable skill set.

The other, not so much.

The first example is a brief but comprehensive breakdown of the candidate’s key skill areas and expertise.

Power words like “developing” and “adopting” are used to convey action and ability.

The second example is unprofessional in its language and lacking necessary detail. We learn next to nothing about the candidate’s actual skill level.

The candidate may be qualified for the position, but an unpolished and vague summary has let them down.

Get your summary right and it will be easier to get the rest of your resume perfect.

To really drive home your abilities, we suggest adding a list of your Areas of Expertise or Key Accomplishments

If you have more experience than your peers in a certain area, this is the place to highlight it.

Example:

• SQL
• Python
• Shell Scripting
• Data Mining
• Analytics
• Detail Oriented
• Optimization
• Communication

Don’t leave out any relevant skills!

As you prepare your list, think about your hard skills and soft skills. Your list should be a balanced offering of both.

Hard skills pertain to your field or profession, those abilities that make you really good at what you do.

Soft skills reflect your personality. They involve skills like critical thinking, leadership qualities, and interpersonal communication.

Make a column for both types of skills.

Check the job description to see how your skills correlate to those being sought.

PRO TIP: Don’t be shy about listing your top skills. Keep them relevant, but also try to focus on your best abilities. Your skills are what sets you apart from all the other applicants out there.

(See below for a helpful table of some suggested hard and soft skill ideas to inspire you in writing your skills section.)

So you’ve written a good summary and listed your expertise points.

Now what?

Now you draft your work experience, the positions you’ve held or hold presently.

This section will probably take up the most space on your data scientist resume page, so let’s be sure you get it right!

Let’s begin!

Layout is crucial. Remember that we are using reverse chronological order.

So this will put your most recent position first, followed by the jobs that came before.

Putting your most recent role first will help your potential employer see how you’ve been utilizing your skills in the present.

It also reveals what point you’re at in your career trajectory.

You should not list every position you’ve ever held, as that would prove tiresome to the reader and not relevant.

Only list those positions that speak to the position you’re seeking.

An exception to this would be if you lack experience in the relevant field.

As you layout your work history, be sure to include:

• The company name
• Where the company is located
• What job you performed there

You should probably include dates of employment for each position, when you started there and when you left.

If you were only employed for a short time, or if you went for long periods between jobs, you may decide to leave dates off your data scientist resume.

However, be aware that you will be asked about dates and time gaps during an interview. So be prepared with answers to such questions.

Next, you will list your day-to-day functions at your jobs using 3-5 relevant bullet points.

The idea is to list the roles you excelled in or were proficient at.

Bullet point examples for reference:

What is your impression of the two examples?

Which candidate would you prefer?

The first example is an effective job entry that demonstrates ability and includes plenty of relevant detail.

Each bullet point begins with a power word that helps to convey confidence and action.

The second example lacks sufficient detail and uses poor language.

The bullet points are confusing rather than helpful.

No real idea of the candidate’s skill level can be determined.

Remember that your work experience entries should demonstrate your competency in action.

PRO TIP: See the job description for power word ideas. Also select roles you performed at your former positions that most closely fit with the job description.

Bots and an ATS

Try to determine if your potential employer is using an Applicant Tracking System (ATS), which utilizes scanning bots to evaluate resumes.

If an ATS is being used, your challenge will be to satisfy the bots.

One method of accomplishing this is to format your work experience section differently.

Use paragraphs instead of bullet points.

From this:

SLP Communications | Los Angeles, CA | Data Scientist | February 2016-Present

• Work with team of Data Scientists to solve problems and analyze data
• Employ predictive analytics and machine learning models to use data
• Collaborate with IT division to monitor model implementation
• Communicate with database using SQL
• Received awards for problem-solving and idea implementation

To this:

Work with a team of Data Scientists to solve problems and analyze data. Employ predictive analytics and machine learning models to utilize data. Maintain close contact with the IT division to monitor model implementation.

Another option would be to use a paragraph along with several bullet points to highlight certain roles or accomplishments.

Work with a team of Data Scientists to solve problems and analyze data. Employ predictive analytics and machine learning models to utilize data. Maintain close contact with the IT division to monitor model implementation.

• Communicate with database using SQL
• Received performance awards for problem solving and idea implementation

A paragraph allows you to utilize language and keywords in ways that will satisfy ATS bots.

However, paragraphs are harder to read for human eyes. It will take a hiring manager twice as long to read versus a list of bullet points.

For this reason, we recommended sticking with bullet points alone unless you happen to be overly concerned about an ATS.

No doubt, your education has played an important role in advancing you in your career.

It is therefore important that you include your education details on your data scientist resume.

Start by listing the highest level of education you received.

Example: Master’s Degree, Bachelor’s Degree, High School Diploma, etc.

Again, use reverse chronological order in listing your education credentials.

Make sure to include your field of study and the name of the college or university you attended.

Include relevant accomplishments, like making the Dean’s List or areas of concentration. Also list minor degrees.
Consider adding your GPA if you’re new to the field and looking to make an impression while you build experience.

Example:

Bachelor of Arts, Computer Science
UC Berkeley, Berkeley, CA
GPA: 4.0
Class of 2011

Remember to add certifications as well, along with any workshops or seminars that have grown your knowledge base and skill set.

Example:

• IBM Data Science Professional Certification, 2012

Additional Sections

Not all of our accomplishments are going to fit onto a resume page.

But perhaps there is a particular accomplishment or award you would like to make a note of, something that doesn’t fit with the other sections on your data scientist resume.

Feel free to make an additional section to list such accomplishments.

Example:

• Awards and honors
• Publications
• Noteworthy Projects
• Social Media Influence
• Speaking Engagements
• Hobbies/Interests
• Volunteer Work

What if You Have No Experience?

If you possess little or no experience in your chosen field, there are some alterations you can make to your resume.

Whether changing careers or starting out, you can still produce an effective data scientist resume that will demonstrate your value.

One formatting option is to move your education section – place it under your summary.

Since you lack experience, your education is going to do a lot in terms of showing your competency and ability.

So you want your credentials near the top of your resume page.

Your work experience is going to be comprised of jobs that are not directly relevant to your new field.

That’s not ideal, but you can still work with what you have.

For instance, you can tailor your bullet points to be as relevant as possible.

Think about roles and functions you’ve done that could prove helpful as a data scientist.

Have you worked with data before?

How about filing and records?

Are you familiar with computers and software?

Have you ever held a job that involved teamwork and communication?

Skill points like these could prove relevant to you in the present!

So don’t leave anything out and really consider the experience you do have.

Include your contact information

It seems obvious, but sometimes it’s easy to forget. Your resume will do no good for you if they have no way of getting touch. Include your email address, phone number, or LinkedIn profile. Whatever is relevant to your situation.

Use space well

A resume is not a lengthy document. So it’s imperative that you get all your important information down. Start with a summary at the top of the page, followed by your skills list, work experience, and education.

Use good power words

Power words will give your resume strength and a sense of action. Use a variety of them and your resume will be sure to stick in the reader’s mind.

Use a trusted proofreader

Acquiring a proofreader could be invaluable. Remember that you want your resume to be as polished as possible. Don’t submit an inferior document with errors.

A few tips about what not to do:

No first person language

While a resume is personal in the sense that it’s about your skills and abilities, it should also be a professional document. To this end, avoid using first person language. This means no “I” or “me” in your writing.

Don’t exceed a single page

One page is all it takes to communicate your skills and work history. Multiple pages are hard to deal with and take a long time to read.

Don’t repeat yourself

Repetition will do you no favors, even if you think you need to repeat something for emphasis. If your resume catches the attention of a hiring manager, they will take time to look it over again. So keep your language fresh.

(We’ve put together a handy table of power words below to use for inspiration.)

No outlandish fonts or formatting

Since readability is a chief goal, don’t use hard-to-read fonts or odd formatting. Let your skills prove your uniqueness!

Data Scientist Resume Power Words

• Work
• Employ
• Maintain
• Communicate
• Received
• Developed
• Utilized
• Analyzed
• Applied
• Recommended
• Used
• Performed
• Created
• Implemented
• Met
• Formulated

Data Scientist Resume Skills List